Development of a Machine Vision-Based Monitoring and Evaluation System for Lodged Wheat

Xiaoyan Liu; ZhongLin Xia; Bin Li

doi:10.48084/etasr.18790

Authors

Xiaoyan Liu School of Mechanical Engineering, Hunan Mechanical and Electrical Polytechnic, China
ZhongLin Xia School of Mechanical Engineering, Hunan Mechanical and Electrical Polytechnic, China
Bin Li School of Mechanical Engineering, Hunan Mechanical and Electrical Polytechnic, China

Volume: 16 | Issue: 3 | Pages: 37070-37076 | June 2026 | https://doi.org/10.48084/etasr.18790

Received: 17 March 2026 | Revised: 24 April 2026 and 11 May 2026 | Accepted: 15 May 2026 | Online: 6 June 2026

Corresponding author: Xiaoyan Liu

Abstract

This study develops an intelligent processing system that integrates monitoring, identification, and assessment of lodged wheat to address yield loss during mechanical harvesting caused by lodging in precision agriculture. This system provides decision support for automatic header adjustment and disaster assessment. The system uses Visual C++ as the integrated development platform and comprehensively applies machine vision technology. Features of the lodged straw layer were enhanced through color difference analysis, linear grayscale transformation, and grayscale inversion. Image enhancement was achieved using median filtering. Precise segmentation of the straw layer and wheat ear layer was realized using mathematical morphology methods (erosion and dilation). Combining Roberts operator edge detection and Hough Transform line detection, lodging boundaries were extracted, and the lodging height difference was calculated. A fully functional software system was successfully developed. The system accurately identifies lodging areas, with detected lodging boundaries showing high conformity to actual conditions, and calculated height difference parameters prove reliable. The system achieved automated processing from image input, providing an effective technical solution for reducing harvest losses in precision agriculture.

Keywords:

precision agriculture, lodged wheat monitoring, machine vision, target segmentation, height difference assessment

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